Some imaging systems (e.g., camera systems employed in conjunction with virtual reality (VR) or augmented reality (AR) devices) project structured light (e.g., predetermined patterns, such as lines, spots, and so on), whether in the visible spectrum, infrared (IR) spectrum, near-infrared (NIR) spectrum, or another wavelength band, into a local area or environment. An imaging subsystem or device may then capture images of the reflections of the projected structured light from the local area. A control system may then process the images to “map” the local area, such as by determining the distance from the imaging subsystem to each lighted portion of the local area based on the geometry of the reflected light patterns perceived via the imaging subsystem. In some systems, this process is referred to as “active triangulation.”
For effective triangulation, the distance between the projector and the imaging subsystem, their relative orientation, and possibly other characteristics associating the projector to the imaging subsystem are inputs for calculations that are typically performed as part of the mapping operation. Generally, small errors in the values of those characteristics may result in significant errors in the generated map of the local area. For example, since many devices that employ mapping position the projector and the imaging subsystem close to each other (e.g., to save space in the device), an error of even a few microns may serve to negatively impact the accuracy of the map. While the device may be closely calibrated, such as by a manufacturer prior to normal operation, subsequent use of the device, including possibly unintended physical shocks or impacts to the device, may change the calibrated or measured characteristics, thus lessening map accuracy.